The association between diabetes and age at the onset of menopause: a systematic review protocol
Bibliographic record
Abstract
Age at the onset of menopause is the most important determinant of women’s future health outcomes. While the basic mechanisms contributing to the onset of menopause are still not fully understood, age at menopause depends on a complex set of various factors. In this regard, the effects of diabetes (DM I/II) on the age at the onset of menopause have received little attention. Electronic databases including PubMed/MEDLINE, Web of Science, Scopus, EMBASE, and Google Scholar will be searched for articles published during January 2000 to August 2018 and containing combinations of related MeSH terms, i.e., “age at menopause” and “diabetes.” Additional studies will also be extracted from the reference lists of the selected papers, gray literature, and key journals in the field. A set of inclusion criteria will be defined, and all eligible observational studies will be included. Two reviewers will independently conduct the study selection, data extraction, and quality assessment of the selected studies. All cases of disagreement will be resolved through consensus. The methodological assessment of the primary studies will be performed based on the Newcastle-Ottawa Scale (NOS). In case of the availability of sufficient data, fixed or random effects models will be used to combine all data. Heterogeneity will be assessed by I 2 statistic and chi-square test. Stata V.11.1 will be used for data analysis (CRD42017080789). This systematic review will not raise any ethical issues. Journal publication and conference presentations will facilitate the wide dissemination of the findings to relevant clinicians and researchers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.084 | 0.079 |
| Meta-epidemiology (narrow) | 0.007 | 0.008 |
| Meta-epidemiology (broad) | 0.020 | 0.015 |
| Bibliometrics | 0.018 | 0.012 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.082 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".